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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59

Characterizing the seismic response of a molten salt nuclear reactor

Abstract One Generation IV nuclear reactor, which uses a fluoride salt as a coolant, graphite reflector blocks as a moderator, and circulating buoyant TRISO pebbles as fuel is at an advanced stage of development. To characterize the seismic behavior of components of this reactor, validate numerical models for analysis, and develop recommendations for design, a set of earthquake‐simulator experiments on a scaled model of the reactor vessel and its internals was executed on a six‐degree‐of‐freedom earthquake simulator. The model was seismically isolated at its base using two types of spherical sliding bearings. The scaled model involved representations of the prototype reactor vessel, core barrel, reflector blocks, coolant, and spherical fuel pebbles. The material and geometric properties of different test components were selected based on a dynamic similitude scaling analysis and an approximate length scale of 0.4. Four sets of three‐component earthquake motions were used as inputs for testing. Instrumentation on the test specimen recorded the dynamic responses of the outer vessel, core barrel, and reflector‐block assembly, the hydrodynamic responses (sloshing and hydrodynamic pressure) of the liquid coolant, pebble consolidation under earthquake shaking, and the behavior of the isolation systems. This paper describes the design of the experiments and presents key results from the tests. The dynamic responses of the outer vessel, core barrel, and the reflector blocks revealed that the components responded as a unit for the intense shaking used in the experiments. The sloshing response of the fluid in a thin annulus near the perimeter of the vessel was heavily damped. The change in the packing fraction of the pebble bed under repeated, intense 3D earthquake shaking was less than 3%. Seismically isolating the vessel substantially reduced demands on its internal components.

Engineering↗

Can Food–Energy–Water Nexus Research Keep Pace with Agricultural Innovation?

The interconnection among food–energy–water (FEW) systems in meeting societal demands is broadly acknowledged. Similarly, competitive or synergistic allocations of water and energy resources for agricultural production, manufacturing, and human consumption are understood, and their economic impacts can be predicted. Far less appreciated and understood are the outcomes of the FEW nexus in response to operation changes in agricultural practices and the associated technological innovations for future generations. Also, the inter-scale and feedback effects of emerging technology-driven resource reallocation and decision-making on FEW systems are largely unknown. For example, how do the agroeconomic feedbacks of intelligent technologies influence the FEW nexus of agricultural production under environmental and demographic changes? How does the necessary water allocation for powering non-powered dams and pumped-storage hydropower generation influence agricultural production and municipal water supply maintenance? How do solar and wind energy farms influence land use for agriculture and the rural economy? In turn, how can the generated solar and wind energy help reduce the cost of groundwater extraction or water desalination?

42 ENGINEERING↗

Multi-Agent Hierarchical Deep Reinforcement Learning for HVAC Control With Flexible DERs

As electricity consumption in commercial and residential buildings continues to rise, reducing energy costs presents an increasing challenge. Heating, ventilating, and air-conditioning (HVAC) systems, which typically account for 40%-50% of a building's energy use, are prime targets for energy savings. Intelligent control of HVAC temperature through the exploitation of HVAC load flexibility brings significant potential to reduce energy consumption and electricity expenses. The nonlinear models of HVAC systems challenge traditional control methods, while the uncertainty introduced by HVAC load flexibility complicates distributed energy resource (DER) management using conventional optimal dispatch techniques. In response to these challenges, we propose a hierarchical multi-agent deep reinforcement learning (DRL) approach. The lower-level agents focus on balancing comfort and energy conservation, while the upper-level DRL agents optimize the use of DERs to reduce peak demand based on the control outcomes of the HVAC by the lower-level agents. Here, in the upper-level agents, we incorporate a multi-agent structure based on ensemble learning, which acts based on historical and current data without relying on precise load forecasting to address the delayed rewarding issue in DRL. This allows for the effective reduction of energy costs. The proposed method is tested using a real-world microgrid comprising 413 buildings in Southern California, and the results demonstrate that our approach can significantly reduce overall electricity bills while ensuring the comfort of consumers and residents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unsteady flow in turbomachinery: An overview

The importance of understanding and modeling the unsteady flow phenomena in turbomachinery is discussed. Historical events in the application and development of gas turbines for aircraft propulsion are traced. Technology advancements over the years are highlighted with focus on the compression system components. Trends in compressor research within the National Advisory Committee for Aeronautics (NACA)/National Aeronautics and Space Administration (NASA) are noted. The impact of technology advancements on the increased occurrences of unsteady flow related problems in advanced engine development programs is discussed. The impact of the new and more demanding requirements being imposed on the propulsion system to meet advanced aircraft mission needs are also noted. Brief discussions on the present day understanding and modeling capability of the unsteady flow phenomena are presented to include discussions on rotating stall, surge, flutter, forced response and noise generation.

Source record↗

Actuator and aerodynamic modeling for high-angle-of-attack aeroservoelasticity

Accurate prediction of airframe/actuation coupling is required by the imposing demands of modern flight control systems. In particular, for agility enhancement at high angle of attack and low dynamic pressure, structural integration characteristics such as hinge moments, effective actuator stiffness, and airframe/control surface damping can have a significant effect on stability predictions. Actuator responses are customarily represented with low-order transfer functions matched to actuator test data, and control surface stiffness is often modeled as a linear spring. The inclusion of the physical properties of actuation and its installation on the airframe is therefore addressed in this paper using detailed actuator models which consider the physical, electrical, and mechanical elements of actuation. The aeroservoelastic analysis procedure is described in which the actuators are modeled as detailed high-order transfer functions and as approximate low-order transfer functions. The impacts of unsteady aerodynamic modeling on aeroservoelastic stability are also investigated in this paper by varying the order of approximation, or number of aerodynamic lag states, in the analysis. Test data from a thrust-vectoring configuration of an F/A-18 aircraft are compared to predictions to determine the effects on accuracy as a function of modeling complexity.

Brenner, Martin J.↗

Actuator and aerodynamic modeling for high-angle-of-attack aeroservoelasticity

Accurate prediction of airframe/actuation coupling is required by the imposing demands of modern flight control systems. In particular, for agility enhancement at high angle of attack and low dynamic pressure, structural integration characteristics such as hinge moments, effective actuator stiffness, and airframe/control surface damping can have a significant effect on stability predictions. Actuator responses are customarily represented with low-order transfer functions matched to actuator test data, and control surface stiffness is often modeled as a linear spring. The inclusion of the physical properties of actuation and its installation on the airframe is therefore addressed using detailed actuator models which consider the physical, electrical, and mechanical elements of actuation. The aeroservoelastic analysis procedure is described in which the actuators are modeled as detailed high-order transfer functions and as approximate low-order transfer functions. The impacts of unsteady aerodynamic modeling on aeroservoelastic stability are also investigated by varying the order of approximation, or number of aerodynamic lag states, in the analysis. Test data from a thrust-vectoring configuration of an F/A-l8 aircraft are compared to predictions to determine the effects on accuracy as a function of modeling complexity.

Brenner, Martin J.↗

Pratt and Whitney/Boeing Engine Validation of Noise Reduction Concepts: Final Report for NASA Contract NAS3-97144, Phase 1

Major airports in the world's air transportation systems face a serious problem in providing greater capacity to meet the ever increasing demands of air travel. This problem could be relieved if airports are allowed to increase their operating time, now restricted by curfews and by relaxing present limits on takeoffs and landings. The key operational issue in extending the present curfews is noise. In response to these increasing restrictive noise regulations, NASA has launched a program to validate through engine testing, noise reduction concepts and technologies that have evolved from the Advanced Subsonic Technologies (AST) Noise Reduction Program. The goal of this AST program was to develop and validate technology that reduces engine noise and improves nacelle suppression effectiveness relative to 1992 technology. Contract NAS3-97144 titled "Engine Validation of Noise Reduction Concepts" (EVNRC) was awarded to P&W on August 12, 1997 to conduct full scale noise reduction tests in two Phases on a PW4098 engine. The following Section 1.2 provides a brief description of the overall program. The remainder of this report provides a detailed documentation of Phase I of the program.

Mathews, Douglas↗

New Crop Selection

For extended space flight, reliable food supplies are a necessity. Most of the food products consumed by astronauts today are stored for flight via freeze drying. Fresh food is needed to supplement known national deficiencies in the stored food diet (Cooper et al.). This is so because stored foods can lose nutritional value. Fresh food is the answer to the nutritional demands of space flight. Kennedy Space Center's Utilization and Life Sciences Office (UB-A), under the Exploration Research and Technology Program (UB), conducts research on plant growth and development under International Space Station (ISS) conditions. UB-A analyzes the growth responses of leafy greens in microgravity and through the manipulation of environmental conditions (CO2 levels, light intensity, relative humidity, and water delivery). By manipulating growing conditions researchers can optimize food production using minimal/restricted resources. The New Crop Selection experiments are testing the suitability of leafy crops to ISS conditions. Results from this study showed that 'Dragoon' Lettuce and 'Red Russian' Kale have the largest fresh mass.

Bhuiyan, Ruqayah H.↗

CMIP6 Historical Simulations (1850‐2014) with GISS‐E2.1

Simulations of the CMIP6 historical period 1850‐‐2014, characterized by the emergence of anthropogenic climate drivers like greenhouse gases, are presented for different configurations of the NASA Goddard Institute for Space Studies (GISS) Earth System ModelE2.1. The GISS‐E2.1 ensembles are more sensitive to forcing than their CMIP5 predecessors (GISS‐E2), but warm less during recent decades due to reduced total forcing. This forcing reduction is attributed to an increase in longwave opacity in pre‐industrial simulations, resulting in an atmosphere less sensitive to further increases in opacity that result from rising greenhouse gas concentrations. This demonstrates the importance of the base climatology to forcing and forced climate trends. Most model versions match observed temperature trends since 1979 from the ocean to the stratosphere. The choice of ocean model is important to the transient climate response, as found in CMIP5 GISS‐E2: the model that more efficiently exports heat to the deep ocean shows a smaller rise in tropospheric temperature. Model sea level rise over the historical period is traced to excessive drawdown of aquifers to meet irrigation demand with a smaller contribution from thermal expansion. This shows how fully coupled models can provide indirect observational constraints upon forcing, in this case, constraining irrigation rates with observed sea level changes. The overall agreement of GISS‐E2.1 with observed trends is familiar from evaluation of its predecessors, as is the conclusion that these trends are almost entirely anthropogenic in origin.

NASA Goddard Institute for Space Studies (GISS) Ea↗

Considerations for Fire Service Response to Residential Battery Energy Storage System Incidents

Renewable energy sources (e.g., rooftop photovoltaics, wind turbines) are capable of addressing our grid-level energy challenges by reducing environmental impacts, increasing resiliency, and increasing the supply of input energy. However, renewable energy sources alone are not a complete solution. The generation of power from major renewable energy sources fluctuates with the weather, creating significant challenges in matching electrical power generation to electrical power consumption. The value of renewable power generation sources is multiplied when paired with battery energy storage systems (ESS), which can store excess power generated from renewable energy sources when it is not consumed and deliver that power later when demand exceeds base power generation. Residential ESS units are frequently installed to support renewable energy initiatives by storing energy from intermittent sources such as photovoltaic panels. Residential ESS units also offer an alternative to gas-powered generators or other backup power means. Lithium-ion batteries are the most common residential ESS technology due to their affordability and energy density. Though lithium-ion systems come with benefits, there is also a risk of thermal runaway within this technology which can result in flammable gas release, fire, and explosion. As the installations of these products increase, the frequency of response to fire incidents involving these products will increase. In response to this new and evolving hazard, UL Solutions (ULS) and UL Fire Safety Research Institute (FSRI) have partnered with the International Association of Fire Fighters (IAFF) to conduct a series of large-scale tests sponsored by the US Department of Energy to characterize the challenges for fire fighters responding to fires involving residential energy storage systems. The project focuses on developing size-up and tactical considerations to support the fire service in navigating the evolving modern fireground.

25 ENERGY STORAGE↗

Ultrafast carrier dynamics in multiple quantum well p–i–n photodiodes

Quantum well (QW) structures are widely used in lasers, semiconductor optical amplifiers, and modulators, enabling their monolithic integration on the same substrate. As optoelectronic systems evolve to meet the growing bandwidth demands in the terahertz regime, a deep understanding of ultrafast carrier dynamics in QW structures becomes essential. We introduce a comprehensive model to analyze the ultrafast dynamics of interband photo-excited carriers in QW p–i–n structures and to calculate their frequency response. This model characterizes the entire photocarrier transport process, including carrier escape from QWs and movement across heterojunction interfaces. Additionally, we outline theoretical methods for calculating carrier escape times from both QWs and heterojunction interfaces. Using a GaAs/AlGaAs QW p–i–n structure as a case study, we discuss the effects of carrier escape times from QWs and heterojunction interfaces, as well as carrier transit time through the intrinsic region, on the frequency response of QW p–i–n structures.

Electronic band structure↗

NASA's Next Generation of Atmospheric Data Science

The Multi-Angle Imager for Aerosols (MAIA) and the Tropospheric Emission: Monitoring of Pollution(TEMPO) are NASA’s next-generation satellite missions for air quality monitoring. These missions will produce high-quality, high-resolution air quality data to support cross-displinary research. The MAIA mission is collaborating with health science researchers and epidemiologists to study the impacts of air quality on health outcomes. TEMPO aims to improve our understanding of tropospheric air pollution chemistry and our ability to make predictions about air quality and climate forcing. TEMPO will offer hourly measurements of tropospheric ozone, aerosols, and clouds focused on North America at high-spatial resolution, while MAIA will produce high-resolution measurements of speciated particulate matter targeting densely populated cities around the globe. Data from these missions will help improve our understanding of the sources, types, and interactions among the aerosols and trace gases that are polluting Earth’s atmosphere, as well as our understanding of the impact of air pollution on pollution on a wide range of important areas including human health, agriculture, weather, and climate change. The challenges of cross-disciplinary research, computationally expensive multi-variate analyses, and high-resolution data at both local and global scales are driving substantial changes across all of NASA’s Distributed Active Archive Centers (DAACs). High resolution data at scales such these requires a new approach to data ingest, archive, and publication. Like other NASA DAACs, the Atmospheric Science Data Center (ASDC), the DAAC that will be responsible for publishing MAIA and TEMPO data products has historically archived and distributed data on premise. DAACs of the future will archive and distribute data in the cloud, enabling them to remake themselves as research-focused data centers that will support on-demand, data-intensive computations for highly accurate retrospective analyses and predictions. Under the new paradigm, data formats and metadata must support on-demand spatial and temporal sub-setting, as well as other data transformation services such as re-gridding and re-sampling. This presentation will discuss work being done to address data formatting and metadata requirements in this dynamic new environment. In addition to the changes in data stewardship practices at the ASDC, the increased focus on supporting scientific research is driving changes in the relationship between DAACs and researchers. While the ASDC will continue to provide first rate data management and stewardship, it is increasingly focused on serving as a partner not only to the science teams that gather and produce the data it publishes, but to the researchers that use that data.

Beth Huffer↗

Low-Cost Radiant Heater for Rapid Response, High-Temperature Heating

High-temperature processing has an irreplaceable role in many research and industrial applications. Despite remarkable development spanning over a century, the pursuit of even higher thermal flux density and more rapid thermal transients has not slowed down. As part of the ongoing energy evolution, many industrial applications are transitioning from direct combustion of fossil fuels as primary energy sources to increasing electrification, capable of adapting to renewable power grids. Thus, there is an emerging need for electrical heaters that can replace burners and supply the heat demand, especially at the highest temperatures. In this study, we report on a radiant heater design that can achieve cyclic heating/cooling rates of up to 400 K min –1 and a temperature range in excess of 1,800 K, comparable to those of commercial infrared gold image furnaces, at high surface and volumetric power densities. The heater consists of a modular unit of incandescent tungsten filament and is enclosed in an evacuated ceramic envelope, chemically inert, tolerant of thermal shock, and impervious to gasses. The material and manufacture cost of such heaters, which is estimated at ~$0.05/W, is less than 0.03% of that for infrared gold image furnaces, which is at >$2/W. Tests of more than 10,000 demanding cycles (high temperature and high heating/cooling rate) over 350 h of total operational time and in different temperature ranges confirm the robust performance of radiant heater prototypes. The design is widely applicable to high-temperature reactor and furnace designs. In thermochemistry research and practice, these radiant heaters could offer multiple benefits compared to solar simulators, lasers, infrared gold furnaces, ceramic heaters, or direct concentration of solar input.

99 GENERAL AND MISCELLANEOUS↗

Generation and Control of Self-Organized Nonlinear Kinetic Structures in High Energy Density Plasmas in the Presence of Intense Magnetic Fields and Ultrashort Laser Pulses

In the project we investigated mechanisms to sculpt phase space by controlling plasma instabilities. We found that linear theory, which applies in the initial growth phase of an instability, allows for initial conditions that can suppress instabilities. This provides a possible mechanism to release the energy available to an instability on demand. We developed various computational techniques that can reduce computational cost of simulations while maintaining or improving physical fidelity. We considered the Buneman instability in the presence of a ponderomotively driven plasma wave to examine the interplay between an instability and steady-state plasma response.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Securing Grid-interactive Efficient Buildings (GEB) through Cyber Defense and Resilient System (CYDRES)

The DOE CYDRES project is driven by the urgent need to address critical research gaps in the domain of cyber-physical security of smart buildings, including Grid-interactive Efficient Buildings (GEBs). CYDRES, a real-time advanced building resilient platform, aims to enhance the cyber-attack-immune capabilities of buildings through multi-layered prevention, detection, and adaptation mechanisms. CYDRES consists of five key modules: a multi-layer network analyzer, an Automatic Fault Detection, Diagnosis, and Prognosis (AFDDP) framework, an intelligent mode selector, a cyber-resilient control framework, and a situation awareness platform. The Network Analyzer employs a data-driven framework that includes a protocol state learning tool and a CRF (Conditional Random Field) command validator. In Hardware-In-the-Loop (HIL) testbeds, it achieved 100% detection accuracy with a false alarm rate of 3%, validating its efficacy in identifying selected cyber-attacks. The AFDDP framework leverages pattern matching, PCA (Principal Component Analysis)-based strategies, and a DBN (Dynamic Bayesian Network)-based fault diagnosis approach to pinpoint the causes of physical system abnormalities using Building Automation System (BAS) data. In HIL experiments, the AFDDP module attained a detection accuracy of over 95% with a false alarm rate below 7%. Additionally, the fault detector utilized machine learning (Random Forest) and deep learning (Multi-Layer Perceptron) methods with acoustic sensor data to achieve a 100% fault detection accuracy in Heating, Ventilation, and Air-Conditioning (HVAC) equipment. The Mode Selector offered real-time impact analysis, allowing immediate actions to protect BASs in the face of emerging threats. The cyber-resilient control framework included an adaptive Model Predictive Control (MPC) and a measurement compensator, reducing temperature violations by up to 94% and improving the total demand flexibility by up to 70% in HIL experiments. Such HIL experiments covered a cyber-attack case and a physical fault case, showcasing CYDRES’ efficiency in maintaining operational continuity during threats. The situation awareness platform in Grafana enhanced real-time threat detection and response visualization, augmenting the operational awareness for building operators. CYDRES demonstrated high technical effectiveness in various test scenarios, particularly in HIL environments. The project's phased development approach ensured efficient use of resources, highlighting its practical feasibility and readiness for commercialization. By enhancing the security and resilience of building operations, CYDRES represents a significant advance in mitigating risks associated with cyber-physical systems, thereby enhancing public confidence in the safety of modern building infrastructure. Future directions for the project include expanding testing protocols, refining AFDDP methodologies, exploring more comprehensive resilient control strategies, and testing in real commercial buildings.

42 ENGINEERING↗

An X-Band Mixer Engineered for 77 K Operation

An X-band Si-diode singly balanced mixer developed specifically for cryogenic operation is presented. In order to reduce thermal demands on a mechanical cooler, the mixer was designed to operate with a minimum of local oscillator (LO) power. That is, since the LO had to be cooled to reduce phase noise, it was desirable to minimize the LO drive. Novel embedding circuit strategy was responsible for nearly theoretical performance. The signal-matching circuit simultaneously provided a reactive termination to the image, sum, and first, second, and third LO harmonic frequencies. A conversion loss of 3.2 dB at 77 K with an LO drive of +1 dBm was measured. This loss included IF filter, dc block, and hybrid coupler losses. Mixer conversion loss is shown to be consistent with the theoretical performance limit expected from the intrinsic diode. The relationship among junction capacitance, flat-band potential, and conversion loss is examined.

Romanofsky, Robert R.↗

Repetition blindness has a perceptual locus: evidence from online processing of targets in RSVP streams

Four experiments tested whether repetition blindness (RB; reduced accuracy reporting repetitions of briefly displayed items) is a perceptual or a memory-recall phenomenon. RB was measured in rapid serial visual presentation (RSVP) streams, with the task altered to reduce memory demands. In Experiment 1 only the number of targets (1 vs. 2) was reported, eliminating the need to remember target identities. Experiment 2 segregated repeated and nonrepeated targets into separate blocks to reduce bias against repeated targets. Experiments 3 and 4 required immediate "online" buttonpress responses to targets as they occurred. All 4 experiments showed very strong RB. Furthermore, the online response data showed clearly that the 2nd of the repeated targets is the one missed. The present results show that in the RSVP paradigm, RB occurs online during initial stimulus encoding and decision making. The authors argue that RB is indeed a perceptual phenomenon.

Form Perception↗

Human-Robot Interaction in High Vulnerability Domains

Future NASA missions will require successful integration of the human with highly complex systems. Highly complex systems are likely to involve humans, automation, and some level of robotic assistance. The complex environments will require successful integration of the human with automation, with robots, and with human-automation-robot teams to accomplish mission critical goals. Many challenges exist for the human performing in these types of operational environments with these kinds of systems. Systems must be designed to optimally integrate various levels of inputs and outputs based on the roles and responsibilities of the human, the automation, and the robots; from direct manual control, shared human-robotic control, or no active human control (i.e. human supervisory control). It is assumed that the human will remain involved at some level. Technologies that vary based on contextual demands and on operator characteristics (workload, situation awareness) will be needed when the human integrates into these systems. Predictive models that estimate the impact of the technologies on the system performance and the on the human operator are also needed to meet the challenges associated with such future complex human-automation-robot systems in extreme environments.

workload↗